Context Awareness of a Smart Device Through Sensing Transient and Continuous Events

2. The method of claim 1, wherein the determining the classification of the transient event based on the second set of feature data includes analyzing the second set of feature data with a plurality of classification parameters.

3. The method of claim 1, wherein the determining the classification of the transient event is conducted at a server communicatively coupled to the smart device.

4. The method of claim 1, further comprising adding time information to the context data received from the one or more sensors.

5. The method of claim 1, further comprising combining the classification of the continuous event and the classification of the transient event to obtain a meta-level context awareness analysis result.

6. The method of claim 5, wherein the combining the classification of the continuous event and the classification of the transient event includes removing at least one of the classification of the continuous event and the classification of the transient event.

7. The method of claim 1, wherein the determining the sequence of the context updates includes using at least one of a finite state machine algorithm or a training model.

9. The method of claim 8, wherein a first classification element in the first motion vector, the first sound vector or the first spatial environment vector lasts shorter than a second classification element in the second motion vector, the second sound vector or the second spatial environment vector, respectively.

11. The smart device of claim 10, wherein the configuring the smart device includes configuring the smart device to automatically conduct an action based on the determined classification of the transient event and the determined classification of the continuous event.

12. The smart device of claim 10, wherein the determining the classification of the transient event based on the second set of feature data includes analyzing the second set of feature data with a plurality of classification parameters.

13. The smart device of claim 10, wherein the actions include adding time information to the context data received from the one or more sensors.

14. The smart device of claim 10, wherein the actions include combining the classification of the continuous event and the classification of the transient event to obtain a meta-level context awareness analysis result.

15. The smart device of claim 14, wherein the combining the classification of the continuous event and the classification of the transient event includes removing at least one of the classification of the continuous event and the classification of the transient event.

17. The system of claim 16, wherein the classification of the transient event is in at least one of a motion vector, a sound vector and a spatial environment vector.

18. The system of claim 16, wherein the generating the first set of feature data includes processing the received context data using a second series of time windows.

19. The system of claim 16, wherein the determining the classification of the transient event based on the second set of feature data includes analyzing the second set of feature data with a plurality of classification parameters.

20. The system of claim 16, wherein the generating the sets of feature data is conducted for context information detected by each of the one or more sensors.